scholarly journals Hippo Pathway Core Genes Based Prognostic Signature and Immune Infiltration Patterns in Lung Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Chang Gu ◽  
Jiafei Chen ◽  
Xuening Dang ◽  
Chunji Chen ◽  
Zhenyu Huang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Hippo Pathway ◽  
Lung Squamous Cell Carcinoma ◽  
Immune Checkpoints ◽  
Immune Infiltration ◽  
Core Genes

BackgroundWe investigated the prognostic effects and their patterns of immune infiltration of hippo pathway core genes in lung squamous cell carcinoma, in order to find some clues for underlying mechanisms of LUSC tumorigenesis and help developing new therapeutic methods.MethodsThe mutational data, transcriptome data and corresponding clinical medical information of LUSC patients were extracted from The Cancer Genome Atlas (TCGA) database. Differential expression genes (DEGs) and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were explored. Survival analysis for the hippo core genes and the prognostic model were performed. Immune infiltration was estimated by CIBERSORT algorithm and some immune checkpoints-related genes were further investigated.ResultsOverall, 551 LUSC samples were included in our study, consisting of 502 LUSC tumor samples and 49 adjacent normal samples, respectively. There were 1910 up-regulated DEGs and 2253 down-regulated DEGs were finally identified. The top five mutational hippo pathway core genes were LATS1 (4%), WWC1 (2%), TAOK1 (2%), TAOK3 (2%), and TAOK2 (2%), respectively. the mutation of LATS2 was highly associated with co-mutational NF2 (P <0.05) and TAOK1 (P <0.05). In survival analyses, we found only WWC1 (log-rank p = 0.046, HR = 1.32, 95% CI = 1–1.73) and LATS2 (log-rank p = 0.013, HR = 1.41, 95%CI = 1.08–1.86) had significant prognostic roles. After getting the three subgroups according to the subtyping results, we demonstrated that T cell gamma delta (p = 5.78e-6), B cell memory (p = 4.61e-4) and T cell CD4+ memory resting (p = 2.65e-5) had significant differences among the three groups. SIGLEC15 (P <0.01) and CD274 (P <0.05) also had statistical differences among the three subgroups.ConclusionsOur study verified the prognostic roles of WWC1 and LATS2 in LUSC patients. Immune checkpoints-related genes SIGLEC15 and CD274 had statistical differences among the three subgroups, which may provide new perceptions on the molecular mechanisms in LUSC and maybe helpful for precisely selecting specific LUSC patients with potential immunotherapy benefits.

scholarly journals Identification of a Prognostic Immune Signature for Esophageal Squamous Cell Carcinoma to Predict Survival and Inflammatory Landscapes

2020 ◽  
Vol 8 ◽  
Author(s):  
Chaoqi Zhang ◽  
Yuejun Luo ◽  
Zhen Zhang ◽  
Zhihui Zhang ◽  
Guochao Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Immune Checkpoints ◽  
Related Risk ◽  
Public Data ◽  
Independent Cohort

Immunotherapy has achieved success in the treatment of esophageal squamous cell carcinoma (ESCC). However, studies concerning immune phenotypes within the ESCC microenvironment and their relationship with prognostic outcomes are limited. We constructed and validated an individual immune-related risk signature for patients with ESCC. We collected 196 ESCC cases, including 119 samples from our previous public data (GSE53624) to use as a training set and an independent cohort with 77 quantitative real-time polymerase chain reaction (qRT-PCR) data, which we used for validation. Head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma (LUSC) cohorts were also collected for validation. A least absolute shrinkage and selection operator (LASSO) model and a stepwise Cox proportional hazards regression model were used to construct the immune-specific signature. The potential mechanism and inflammatory landscapes of the signature were explored using bioinformatics and immunofluorescence assay methods. This signature predicted different prognoses in clinical subgroups and the independent cohort, as well as in patients with HNSCC and LUSC. Further exploration revealed that the signature was associated with specific inflammatory activities (activation of macrophages and T-cell signaling transduction). Additionally, high-risk patients exhibited distinctive immune checkpoints panel and higher regulatory T cell and fibroblast infiltration. This signature served as an independent prognostic factor in ESCC. This was the first applicable immune-related risk signature for ESCC. Our results furnished new hints of immune profiling of ESCC, which may provide some clues to further optimize associated cancer immunotherapies.

scholarly journals The Oncogenic Role and Immune Infiltration for CARM1 Identified by Pancancer Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kui Liu ◽  
Jing Ma ◽  
Jiao Ao ◽  
Lili Mu ◽  
Yixian Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Progression ◽  
Squamous Cell ◽  
Immune Modulation ◽  
Lung Squamous Cell Carcinoma ◽  
Predictive Biomarker ◽  
Protein Arginine Methyltransferases ◽  
Immune Infiltration ◽  
T Cell Infiltration

Chromatin-modifying enzymes, especially protein arginine methyltransferases (PRMTs), have been identified as candidate targets for cancer. Cellular or animal-based evidence has suggested an association between coactivator-linked arginine methyltransferase 1 (CARM1) and cancer progression. However, the relationship between CARM1 and patient prognosis and immune infiltration in pancancer patients is unknown. On the basis of the GEO and TCGA databases, we first investigated the possible oncogenic functions of CARM1 in thirty-three tumor types. CARM1 expression was elevated in many types of tumors. In addition, there was a significant association between CARM1 expression and the survival rate of tumor patients. Uterine corpus endometrial carcinoma (UCES) samples had the highest CARM1 mutation frequency of all cancer types. In head and neck squamous cell carcinoma (HNSC) and lung squamous cell carcinoma (LUSC), CARM1 expression was associated with the level of CD8+ T cell infiltration, and cancer-associated fibroblast infiltration was also observed in other tumors including kidney renal papillary cell carcinoma (KIRC) and prostate adenocarcinoma (PRAD). CARM1 was involved in immune modulation and played an important role in the tumor microenvironment (TME). Furthermore, activities associated with RNA transport and its metabolism were included in the possible mechanisms of CARM1. Herein, our first pancancer research explores the oncogenic role of CARM1 in various tumors. CARM1 is associated with immune infiltrates and can be employed as a predictive biomarker in pancancer.

scholarly journals Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Yao ◽  
Tingting Zhang ◽  
Lingyu Qi ◽  
Ruijuan Liu ◽  
Gongxi Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cerna Network

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

scholarly journals Identification of Biomarkers Related to CD8+ T Cell Infiltration With Gene Co-expression Network in Lung Squamous Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Min Tang ◽  
Yukun Li ◽  
Xianyu Luo ◽  
Jiao Xiao ◽  
Juan Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Cell Infiltration ◽  
Hub Genes ◽  
T Cell Infiltration ◽  
Potential Biomarker

Lung squamous cell carcinoma (LSCC) is one of the most common types of lung cancer in adults worldwide. With the development of modern medicine, cancer treatment that harnesses the power of the immune system might be particularly effective for treating LSCC. In this research, LSCC expression data, which quantify the cellular composition of immune cells, were analyzed by weighted gene coexpression network analysis (WGCNA) and a deconvolution algorithm based on the Gene Expression Omnibus (GEO) database, and the results indicated a close relationship between LSCC and CD8+ T cells. Six hub genes (SYT3, METTL8, HSPB3, GFM1, ERLIN2, and CLCN2) were verified by gene–gene network and protein–protein interaction (PPI) network analyses. We found that the six hub genes were increased in cancer tissues and were closely correlated with cancer development and progression. After immune correlation analysis, METTL8 was selected as a prognostic biomarker. Finally, we found that the METTL8 levels were increased in multiple lung cancer cell lines and LSCC tissues. METTL8 inhibition could clearly induce G1 cell cycle arrest and suppress proliferation. Therefore, METTL8, which is related to CD8+ T cell infiltration, might be identified as a potential biomarker and gene therapy target in LSCC.

scholarly journals Identification of lncRNAs associated with lung squamous cell carcinoma prognosis in the competitive endogenous RNA network

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7727 ◽  
Author(s):  
Lingyu Qi ◽  
Tingting Zhang ◽  
Yan Yao ◽  
Jing Zhuang ◽  
Cun Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Molecular Mechanisms ◽  
Lung Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Verification Methods ◽  
Competitive Endogenous Rna

Background Long noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients. Materials and Methods The RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA. Results Datasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC. Conclusion In present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.

scholarly journals Characterization of lung squamous cell carcinoma-derived t-cell suppressive factor

Cancer ◽  
1993 ◽  
Vol 72 (8) ◽  
pp. 2347-2357 ◽  
Author(s):  
Ichiro Yoshino ◽  
Genki Kimura ◽  
Tokujiro Yano ◽  
Masahiro Miyamoto ◽  
Kikuo Nomoto ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma

scholarly journals A Ferroptosis-Related Long Non-Coding RNA Signature Predicts Prognosis and Immune Microenvironment for Lung Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Zhiyang Liu ◽  
Zhongcheng Xie ◽  
Chenxi Zhi ◽  
Xiaoyan Lin ◽  
Wentao Ma ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk ◽  
Immune Checkpoints

Abstract Background: Ferroptosis-related lncRNAs (FerLncRNAs) were developed to play a significant role in cancer treatment and prognosis. However, the relationship between FerLncRNAs and Lung squamous cell carcinoma (LUSC) remains unclear.Method: Based on ferroptosis-related differentially expressed lncRNAs in LUSC, we established a prognostic 8-lncRNA signature.Results: 8 Ferroptosis-related lncRNAs (LUCAT1, AL161431.1, AL122125.1, AC104248.1, AC016924.1, MIR3945HG, C10orf55 and AP006545.2) had prognostic value for LUSC by multivariate COX analysis (P<0.05), and possessed significant association with patient outcomes. Kaplan–Meier curves showed an obvious difference in OS that the high-risk group patients exhibited poorer survival than the low-risk group patients. The clinical receiver operating characteristic (ROC) curve and decision curve analysis (DCA) revealed that the ferroptosis-related lncRNAs prognostic signature can (FerRLSig) emerged more outstanding performance than clinical features in predicting the prognosis of LUSC. GSEA revealed that the majority of the novel Ferroptosis-related lncRNAs signature-regulated immune responses and the immune system processes were enriched in the high-risk group. 34 immune checkpoints (ICs) were detected significantly different expression between high-risk and low-risk groups.Conclusion: A novel FerRLSig based on 8 Ferroptosis-related lncRNAs provided important prognostic value for LUSC patients and developed new insights about ferroptosis-related immunotherapy targets in clinic.

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